Concatenate pandas Data frame with Series and multiply the second element
I have a pandas data frame with many rows and columns like this
Name Skill Age
Adam C++ 23
Beth Java 25
Micheal Scala 21
...
Aaron Erlang 23
I have another list from which i can create a pandas series
dept = ['Country', 'UK']
pd.Series[dept]
s = pd.Series(dept)
Now i want to concat the dataframe and the Series with Second element of the list should be repeated.
Name Skill Age Country
Adam C++ 23 UK
Beth Java 25 UK
Micheal Scala 21 UK
...
Aaron Erlang 23 UK
UK should be repeated and the Country should become the label for the series.
I am clueless on how to achieve this
python-3.x pandas
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
add a comment |
I have a pandas data frame with many rows and columns like this
Name Skill Age
Adam C++ 23
Beth Java 25
Micheal Scala 21
...
Aaron Erlang 23
I have another list from which i can create a pandas series
dept = ['Country', 'UK']
pd.Series[dept]
s = pd.Series(dept)
Now i want to concat the dataframe and the Series with Second element of the list should be repeated.
Name Skill Age Country
Adam C++ 23 UK
Beth Java 25 UK
Micheal Scala 21 UK
...
Aaron Erlang 23 UK
UK should be repeated and the Country should become the label for the series.
I am clueless on how to achieve this
python-3.x pandas
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
1
what about thisdf['Country']='UK'without a series
– Mohamed Thasin ah
Jan 2 at 9:33
@MohamedThasinah exactly. @jhon.smith no need forseries
– meW
Jan 2 at 9:34
Possible duplicate of Set value to an entire column of a pandas dataframe
– anky_91
Jan 2 at 9:43
Hey Mohamed Thanks that's brilliant i was stupid not to think of an simple and elegant solution
– jhon.smith
Jan 4 at 13:25
add a comment |
I have a pandas data frame with many rows and columns like this
Name Skill Age
Adam C++ 23
Beth Java 25
Micheal Scala 21
...
Aaron Erlang 23
I have another list from which i can create a pandas series
dept = ['Country', 'UK']
pd.Series[dept]
s = pd.Series(dept)
Now i want to concat the dataframe and the Series with Second element of the list should be repeated.
Name Skill Age Country
Adam C++ 23 UK
Beth Java 25 UK
Micheal Scala 21 UK
...
Aaron Erlang 23 UK
UK should be repeated and the Country should become the label for the series.
I am clueless on how to achieve this
python-3.x pandas
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
I have a pandas data frame with many rows and columns like this
Name Skill Age
Adam C++ 23
Beth Java 25
Micheal Scala 21
...
Aaron Erlang 23
I have another list from which i can create a pandas series
dept = ['Country', 'UK']
pd.Series[dept]
s = pd.Series(dept)
Now i want to concat the dataframe and the Series with Second element of the list should be repeated.
Name Skill Age Country
Adam C++ 23 UK
Beth Java 25 UK
Micheal Scala 21 UK
...
Aaron Erlang 23 UK
UK should be repeated and the Country should become the label for the series.
I am clueless on how to achieve this
python-3.x pandas
python-3.x pandas
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
asked Jan 2 at 9:32
jhon.smithjhon.smith
79741534
79741534
1
what about thisdf['Country']='UK'without a series
– Mohamed Thasin ah
Jan 2 at 9:33
@MohamedThasinah exactly. @jhon.smith no need forseries
– meW
Jan 2 at 9:34
Possible duplicate of Set value to an entire column of a pandas dataframe
– anky_91
Jan 2 at 9:43
Hey Mohamed Thanks that's brilliant i was stupid not to think of an simple and elegant solution
– jhon.smith
Jan 4 at 13:25
add a comment |
1
what about thisdf['Country']='UK'without a series
– Mohamed Thasin ah
Jan 2 at 9:33
@MohamedThasinah exactly. @jhon.smith no need forseries
– meW
Jan 2 at 9:34
Possible duplicate of Set value to an entire column of a pandas dataframe
– anky_91
Jan 2 at 9:43
Hey Mohamed Thanks that's brilliant i was stupid not to think of an simple and elegant solution
– jhon.smith
Jan 4 at 13:25
1
1
what about this
df['Country']='UK' without a series– Mohamed Thasin ah
Jan 2 at 9:33
what about this
df['Country']='UK' without a series– Mohamed Thasin ah
Jan 2 at 9:33
@MohamedThasinah exactly. @jhon.smith no need for
series– meW
Jan 2 at 9:34
@MohamedThasinah exactly. @jhon.smith no need for
series– meW
Jan 2 at 9:34
Possible duplicate of Set value to an entire column of a pandas dataframe
– anky_91
Jan 2 at 9:43
Possible duplicate of Set value to an entire column of a pandas dataframe
– anky_91
Jan 2 at 9:43
Hey Mohamed Thanks that's brilliant i was stupid not to think of an simple and elegant solution
– jhon.smith
Jan 4 at 13:25
Hey Mohamed Thanks that's brilliant i was stupid not to think of an simple and elegant solution
– jhon.smith
Jan 4 at 13:25
add a comment |
1 Answer
1
active
oldest
votes
Select values of list by indexing for column name and for values:
dept = ['Country', 'UK']
df[dept[0]] = dept[1]
print (df)
Name Skill Age Country
0 Adam C++ 23 UK
1 Beth Java 25 UK
2 Micheal Scala 21 UK
3 Aaron Erlang 23 UK
If input data is Series select by position by Series.iat:
s = pd.Series(dept)
df[s.iat[0]] = s.iat[1]
#if default RangeIndex
#df[s[0]] = s[1]
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
add a comment |
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1 Answer
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active
oldest
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1 Answer
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active
oldest
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oldest
votes
active
oldest
votes
Select values of list by indexing for column name and for values:
dept = ['Country', 'UK']
df[dept[0]] = dept[1]
print (df)
Name Skill Age Country
0 Adam C++ 23 UK
1 Beth Java 25 UK
2 Micheal Scala 21 UK
3 Aaron Erlang 23 UK
If input data is Series select by position by Series.iat:
s = pd.Series(dept)
df[s.iat[0]] = s.iat[1]
#if default RangeIndex
#df[s[0]] = s[1]
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
add a comment |
Select values of list by indexing for column name and for values:
dept = ['Country', 'UK']
df[dept[0]] = dept[1]
print (df)
Name Skill Age Country
0 Adam C++ 23 UK
1 Beth Java 25 UK
2 Micheal Scala 21 UK
3 Aaron Erlang 23 UK
If input data is Series select by position by Series.iat:
s = pd.Series(dept)
df[s.iat[0]] = s.iat[1]
#if default RangeIndex
#df[s[0]] = s[1]
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
add a comment |
Select values of list by indexing for column name and for values:
dept = ['Country', 'UK']
df[dept[0]] = dept[1]
print (df)
Name Skill Age Country
0 Adam C++ 23 UK
1 Beth Java 25 UK
2 Micheal Scala 21 UK
3 Aaron Erlang 23 UK
If input data is Series select by position by Series.iat:
s = pd.Series(dept)
df[s.iat[0]] = s.iat[1]
#if default RangeIndex
#df[s[0]] = s[1]
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
Select values of list by indexing for column name and for values:
dept = ['Country', 'UK']
df[dept[0]] = dept[1]
print (df)
Name Skill Age Country
0 Adam C++ 23 UK
1 Beth Java 25 UK
2 Micheal Scala 21 UK
3 Aaron Erlang 23 UK
If input data is Series select by position by Series.iat:
s = pd.Series(dept)
df[s.iat[0]] = s.iat[1]
#if default RangeIndex
#df[s[0]] = s[1]
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
edited Jan 2 at 9:42
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
answered Jan 2 at 9:36
jezraeljezrael
345k25300371
345k25300371
add a comment |
add a comment |
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1
what about this
df['Country']='UK'without a series– Mohamed Thasin ah
Jan 2 at 9:33
@MohamedThasinah exactly. @jhon.smith no need for
series– meW
Jan 2 at 9:34
Possible duplicate of Set value to an entire column of a pandas dataframe
– anky_91
Jan 2 at 9:43
Hey Mohamed Thanks that's brilliant i was stupid not to think of an simple and elegant solution
– jhon.smith
Jan 4 at 13:25